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FinO domain proteins such as ProQ of the model pathogen Salmonella enterica have emerged as a new class of major RNA-binding proteins in bacteria. ProQ has been shown to target hundreds of transcripts, including mRNAs from many virulence regions, but its role, if any, in bacterial pathogenesis has not been studied. Here, using a Dual RNA-seq approach to profile ProQ-dependent gene expression changes as Salmonella infects human cells, we reveal dysregulation of bacterial motility, chemotaxis, and virulence genes which is accompanied by altered MAPK (mitogen-activated protein kinase) signaling in the host. Comparison with the other major RNA chaperone in Salmonella, Hfq, reinforces the notion that these two global RNA-binding proteins work in parallel to ensure full virulence. Of newly discovered infection-associated ProQ-bound small noncoding RNAs (sRNAs), we show that the 3′UTR-derived sRNA STnc540 is capable of repressing an infection-induced magnesium transporter mRNA in a ProQ-dependent manner. Together, this comprehensive study uncovers the relevance of ProQ for Salmonella pathogenesis and highlights the importance of RNA-binding proteins in regulating bacterial virulence programs.
IMPORTANCE
The protein ProQ has recently been discovered as the centerpiece of a previously overlooked “third domain” of small RNA-mediated control of gene expression in bacteria. As in vitro work continues to reveal molecular mechanisms, it is also important to understand how ProQ affects the life cycle of bacterial pathogens as these pathogens infect eukaryotic cells. Here, we have determined how ProQ shapes Salmonella virulence and how the activities of this RNA-binding protein compare with those of Hfq, another central protein in RNA-based gene regulation in this and other bacteria. To this end, we apply global transcriptomics of pathogen and host cells during infection. In doing so, we reveal ProQ-dependent transcript changes in key virulence and host immune pathways. Moreover, we differentiate the roles of ProQ from those of Hfq during infection, for both coding and noncoding transcripts, and provide an important resource for those interested in ProQ-dependent small RNAs in enteric bacteria.
Background:
Employees insured in pension insurance, who are incapable of working due to ill health, are entitled to a disability pension. To assess whether an individual meets the medical requirements to be considered as disabled, a work capacity evaluation is conducted. However, there are no official guidelines on how to perform an external quality assurance for this evaluation process. Furthermore, the quality of medical reports in the field of insurance medicine can vary substantially, and systematic evaluations are scarce. Reliability studies using peer review have repeatedly shown insufficient ability to distinguish between high, moderate and low quality. Considering literature recommendations, we developed an instrument to examine the quality of medical experts’reports.
Methods:
The peer review manual developed contains six quality domains (formal structure, clarity, transparency, completeness, medical-scientific principles, and efficiency) comprising 22 items. In addition, a superordinate criterion (survey confirmability) rank the overall quality and usefulness of a report. This criterion evaluates problems of innerlogic and reasoning. Development of the manual was assisted by experienced physicians in a pre-test. We examined the observable variance in peer judgements and reliability as the most important outcome criteria. To evaluate inter-rater reliability, 20 anonymous experts’ reports detailing the work capacity evaluation were reviewed by 19 trained raters (peers). Percentage agreement and Kendall’s W, a reliability measure of concordance between two or more peers, were calculated. A total of 325 reviews were conducted.
Results:
Agreement of peer judgements with respect to the superordinate criterion ranged from 29.2 to 87.5%. Kendall’s W for the quality domain items varied greatly, ranging from 0.09 to 0.88. With respect to the superordinate criterion, Kendall’s W was 0.39, which indicates fair agreement. The results of the percentage agreement revealed systemic peer preferences for certain deficit scale categories.
Conclusion:
The superordinate criterion was not sufficiently reliable. However, in comparison to other reliability studies, this criterion showed an equivalent reliability value. This report aims to encourage further efforts to improve evaluation instruments. To reduce disagreement between peer judgments, we propose the revision of the peer review instrumentand the development and implementation of a standardized rater training to improve reliability.
To understand the gene regulation of an organism of interest, a comprehensive genome annotation is essential. While some features, such as coding sequences, can be computationally predicted with high accuracy based purely on the genomic sequence, others, such as promoter elements or noncoding RNAs, are harder to detect. RNA sequencing (RNA-seq) has proven to be an efficient method to identify these genomic features and to improve genome annotations. However, processing and integrating RNA-seq data in order to generate high-resolution annotations is challenging, time consuming, and requires numerous steps. We have constructed a powerful and modular tool called ANNOgesic that provides the required analyses and simplifies RNA-seq-based bacterial and archaeal genome annotation. It can integrate data from conventional RNA-seq and differential RNA-seq and predicts and annotates numerous features, including small noncoding RNAs, with high precision. The software is available under an open source license (ISCL) at https://pypi.org/project/ANNOgesic/.
Background:
The German quality assurance programme for evaluating work capacity is based on peer review that evaluates the quality of medical experts' reports. Low reliability is thought to be due to systematic differences among peers. For this purpose, we developed a curriculum for a standardized peer-training (SPT). This study investigates, whether the SPT increases the inter-rater reliability of social medical physicians participating in a cross-institutional peer review.
Methods:
Forty physicians from 16 regional German Pension Insurances were subjected to SPT. The three-day training course consist of nine educational objectives recorded in a training manual. The SPT is split into a basic module providing basic information about the peer review and an advanced module for small groups of up to 12 peers training peer review using medical reports. Feasibility was tested by assessing selection, comprehensibility and subjective use of contents delivered, the trainers' delivery and design of training materials. The effectiveness of SPT was determined by evaluating peer concordance using three anonymised medical reports assessed by each peer. Percentage agreement and Fleiss' kappa (κ\(_m\)) were calculated. Concordance was compared with review results from a previous unstructured, non-standardized peer-training programme (control condition) performed by 19 peers from 12 German Pension Insurances departments. The control condition focused exclusively on the application of peer review in small groups. No specifically training materials, methods and trainer instructions were used.
Results:
Peer-training was shown to be feasible. The level of subjective confidence in handling the peer review instrument varied between 70 and 90%. Average percentage agreement for the main outcome criterion was 60.2%, resulting in a κ\(_m\) of 0.39. By comparison, the average percentage concordance was 40.2% and the κ\(_m\) was 0.12 for the control condition.
Conclusion:
Concordance with the main criterion was relevant but not significant (p = 0.2) higher for SPT than for the control condition. Fleiss' kappa coefficient showed that peer concordance was higher for SPT than randomly expected. Nevertheless, a score of 0.39 for the main criterion indicated only fair inter-rater reliability, considerably lower than the conventional standard of 0.7 for adequate reliability.
The transcriptome is a powerful proxy for the physiological state of a cell, healthy or diseased. As a result, transcriptome analysis has become a key tool in understanding the molecular changes that accompany bacterial infections of eukaryotic cells. Until recently, such transcriptomic studies have been technically limited to analyzing mRNA expression changes in either the bacterial pathogen or the infected eukaryotic host cell. However, the increasing sensitivity of high-throughput RNA sequencing now enables “dual RNA-seq” studies, simultaneously capturing all classes of coding and noncoding transcripts in both the pathogen and the host. In the five years since the concept of dual RNA-seq was introduced, the technique has been applied to a range of infection models. This has not only led to a better understanding of the physiological changes in pathogen and host during the course of an infection but has also revealed hidden molecular phenotypes of virulence-associated small noncoding RNAs that were not visible in standard infection assays. Here, we use the knowledge gained from these recent studies to suggest experimental and computational guidelines for the design of future dual RNA-seq studies. We conclude this review by discussing prospective applications of the technique.
Many pathogenic bacteria utilize specialized secretion systems to deliver proteins called effectors into eukaryotic cells for manipulation of host pathways. The vast majority of known effector targets are host proteins, whereas a potential targeting of host nucleic acids remains little explored. There is only one family of effectors known to target DNA directly, and effectors binding host RNA are unknown. Here, we take a two-pronged approach to search for RNA-binding effectors, combining biocomputational prediction of RNA-binding domains (RBDs) in a newly assembled comprehensive dataset of bacterial secreted proteins, and experimental screening for RNA binding in mammalian cells. Only a small subset of effectors were predicted to carry an RBD, indicating that if RNA targeting was common, it would likely involve new types of RBDs. Our experimental evaluation of effectors with predicted RBDs further argues for a general paucity of RNA binding activities amongst bacterial effectors. We obtained evidence that PipB2 and Lpg2844, effector proteins of Salmonella and Legionella species, respectively, may harbor novel biochemical activities. Our study presenting the first systematic evaluation of the RNA-targeting potential of bacterial effectors offers a basis for discussion of whether or not host RNA is a prominent target of secreted bacterial proteins.
RNA-binding proteins (RBPs) have been established as core components of several post-transcriptional gene regulation mechanisms. Experimental techniques such as cross-linking and co-immunoprecipitation have enabled the identification of RBPs, RNA-binding domains (RBDs) and their regulatory roles in the eukaryotic species such as human and yeast in large-scale. In contrast, our knowledge of the number and potential diversity of RBPs in bacteria is poorer due to the technical challenges associated with the existing global screening approaches. We introduce APRICOT, a computational pipeline for the sequence-based identification and characterization of proteins using RBDs known from experimental studies. The pipeline identifies functional motifs in protein sequences using position-specific scoring matrices and Hidden Markov Models of the functional domains and statistically scores them based on a series of sequence-based features. Subsequently, APRICOT identifies putative RBPs and characterizes them by several biological properties. Here we demonstrate the application and adaptability of the pipeline on large-scale protein sets, including the bacterial proteome of Escherichia coli. APRICOT showed better performance on various datasets compared to other existing tools for the sequence-based prediction of RBPs by achieving an average sensitivity and specificity of 0.90 and 0.91 respectively. The command-line tool and its documentation are available at https://pypi.python.org/pypi/bio-apricot.
The primary transcriptome of Neisseria meningitidis and its interaction with the RNA chaperone Hfq
(2017)
Neisseria meningitidis is a human commensal that can also cause life-threatening meningitis and septicemia. Despite growing evidence for RNA-based regulation in meningococci, their transcriptome structure and output of regulatory small RNAs (sRNAs) are incompletely understood. Using dRNA-seq, we have mapped at single-nucleotide resolution the primary transcriptome of N. meningitidis strain 8013. Annotation of 1625 transcriptional start sites defines transcription units for most protein-coding genes but also reveals a paucity of classical σ70-type promoters, suggesting the existence of activators that compensate for the lack of −35 consensus sequences in N. meningitidis. The transcriptome maps also reveal 65 candidate sRNAs, a third of which were validated by northern blot analysis. Immunoprecipitation with the RNA chaperone Hfq drafts an unexpectedly large post-transcriptional regulatory network in this organism, comprising 23 sRNAs and hundreds of potential mRNA targets. Based on this data, using a newly developed gfp reporter system we validate an Hfq-dependent mRNA repression of the putative colonization factor PrpB by the two trans-acting sRNAs RcoF1/2. Our genome-wide RNA compendium will allow for a better understanding of meningococcal transcriptome organization and riboregulation with implications for colonization of the human nasopharynx.
Model enteric bacteria such as Escherichia coli and Salmonella enterica express hundreds of small non-coding RNAs (sRNAs), targets for most of which are yet unknown. Some sRNAs are remarkably well conserved, indicating that they serve cellular functions that go beyond the necessities of a single species. One of these ‘core sRNAs’ of largely unknown function is the abundant ∼100-nucleotide SdsR sRNA which is transcribed by the general stress σ-factor, σ\(^{S}\) and accumulates in stationary phase. In Salmonella, SdsR was known to inhibit the synthesis of the species-specific porin, OmpD. However, sdsR genes are present in almost all enterobacterial genomes, suggesting that additional, conserved targets of this sRNA must exist. Here, we have combined SdsR pulse-expression with whole genome transcriptomics to discover 20 previously unknown candidate targets of SdsR which include mRNAs coding for physiologically important regulators such as the carbon utilization regulator, CRP, the nucleoid-associated chaperone, StpA and the antibiotic resistance transporter, TolC. Processing of SdsR by RNase E results in two cellular SdsR variants with distinct target spectra. While the overall physiological role of this orphan core sRNA remains to be fully understood, the new SdsR targets present valuable leads to determine sRNA functions in resting bacteria.
An expanded evaluation of protein function prediction methods shows an improvement in accuracy
(2016)
Background
A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging.
Results
We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2.
Conclusions
The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent.